Development and evaluation of a primary care antimicrobial stewardship program (PC-ASP) in Toronto, Ontario, Canada
Bibliographic record
Abstract
Background: Effective community-based antimicrobial stewardship programs (ASPs) are needed because 90% of antimicrobials are prescribed in the community. A primary care ASP (PC-ASP) was evaluated for its effectiveness in lowering antibiotic prescriptions for six common infections. Methods: A multi-faceted educational program was assessed using a before-and-after design in four primary care clinics from 2015 through 2017. The primary outcome was the difference between control and intervention clinics in total antibiotic prescriptions for six common infections before and after the intervention. Secondary outcomes included changes in condition-specific antibiotic use, delayed antibiotic prescriptions, prescriptions exceeding 7 days duration, use of recommended antibiotics, and emergency department visits or hospitalizations within 30 days. Multi-method models adjusting for demographics, case mix, and clustering by physician were used to estimate treatment effects. Results: Total antibiotic prescriptions in control and intervention clinics did not differ (difference in differences = 1.7%; 95% CI –12.5% to 15.9%), nor did use of delayed prescriptions (–5.2%; 95% CI –24.2% to 13.8%). Prescriptions for longer than 7 days were significantly reduced (–21.3%; 95% CI –42.5% to –0.1%). However, only 781 of 1,777 encounters (44.0%) involved providers who completed the ASP education. Where providers completed the education, delayed prescriptions increased 17.7% ( p = 0.06), and prescriptions exceeding 7 days duration declined (–27%; 95% CI –48.3% to –5.6%). Subsequent emergency department visits and hospitalizations did not increase. Conclusions: PC-ASP effectiveness on antibiotic use was variable. Shorter prescription durations and increased use of delayed prescriptions were adopted by engaged primary care providers.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".